Saturn Ramenskoye vs Fakel II: result 2-0 and analysis
Second League - Group 3Group 3 - 12Kick-off on October 24, 2020 at 02:00 PM (UTC)Leon Arena, Ramenskoe
Full time
What was the result of Saturn Ramenskoye vs Fakel II?
Saturn Ramenskoye won 2-0 on October 24, 2020.
Goalscorers
- 14′Konstantin KorzhSaturn Ramenskoye
- 27′Konstantin KorzhSaturn Ramenskoye
What is the recent form of both teams?
Over their last 15 matches in all competitions, Saturn Ramenskoye have 7 wins, 3 draws and 5 defeats; Fakel II have 2, 0 and 9.
The competition is shown for every match: in pre-season, several of these games are friendlies.
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 18, 2020 | Khimik-Arsenal(away) | 3-0 | Second League - Group 3 |
| Oct 11, 2020 | Kaluga(home) | 2-0 | Second League - Group 3 |
| Oct 4, 2020 | Ryazan(away) | 4-1 | Second League - Group 3 |
| Sep 27, 2020 | Avangard Kursk(home) | 5-0 | Second League - Group 3 |
| Sep 20, 2020 | Krasnyy-SGAFKST(away) | 1-1 | Second League - Group 3 |
| Date | Opponent | Score | Competition |
|---|---|---|---|
| Oct 18, 2020 | Kaluga(away) | 1-4 | Second League - Group 3 |
| Oct 11, 2020 | Avangard Kursk(home) | 1-0 | Second League - Group 3 |
| Oct 4, 2020 | FK Sokol Saratov(away) | 0-1 | Second League - Group 3 |
| Sep 27, 2020 | Metallurg Vidnoye(home) | 2-1 | Second League - Group 3 |
| Sep 20, 2020 | Sakhalin(away) | 1-5 | Second League - Group 3 |
How many goals should we expect?
Saturn Ramenskoye score 1.8 and concede 1.2 goals per match over their last 15; Fakel II score 0.8 and concede 2.3.
| Club | Goals scored / match | Goals conceded / match | Clean sheets | Both teams scored | Over 2.5 goals |
|---|---|---|---|---|---|
| Saturn Ramenskoye | 1.8 | 1.2 | 6 | 6/15 | 9/15 |
| Fakel II | 0.8 | 2.3 | 1 | 5/11 | 6/11 |
Over the last 15 matches in all competitions.
Where do both teams sit in the table?
| # | Club | P | W | D | L | GF | GA | Pts |
|---|---|---|---|---|---|---|---|---|
| 6 | Saturn Ramenskoye | 20 | 10 | 4 | 6 | 36 | 30 | 34 |
How does Footlab compute this prediction?
The model combines both teams' Elo ratings (anchored by competition pool), their recent form weighted by opponent strength, home advantage and a Poisson matrix for scorelines. Its accuracy is measured continuously on the predictions actually published. Methodology and measured accuracy